Extraction Opinion of Social Media in Higher Education Using Sentiment Analysis

Authors

    Thomas Edison Tarigan( 1 ) Robby C Buwono( 2 ) Sri Redjeki( 3 )

    (1) STMIK AKAKOM
    (2) STMIK Akakom
    (3) STMIK Akakom

DOI:


https://doi.org/10.32877/bt.v2i1.92

Keywords:


NBC, Sentiment Analysis, Opinion Mining, Twitter

Abstract

The purpose of this research is to extract social media Twitter opinion on a tertiary institution using sentiment analysis. The results of sentiment analysis will provide input to universities as a form of evaluation of management performance in managing institutions. Sentiment analysis generated using the Naïve Bayes Classifier method which is classified into 4 classes: positive, normal, negative and unknown. This study uses 1000 data tweets used for training data needs. The data is classified manually to determine the sentiment of the tweet. Then 20 tweet data is used for testing.

The results of this study produce a system that can classify sentiments automatically with 75% test results for sentiment, some obstacles in processing real-time tweets such as duplicate tweets (spam tweets), Indonesian structures that are quite complex and diverse.

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Published

2019-10-30

How to Cite

[1]
T. E. Tarigan, R. C. Buwono, and S. Redjeki, “Extraction Opinion of Social Media in Higher Education Using Sentiment Analysis”, bit-Tech, vol. 2, no. 1, pp. 11–19, Oct. 2019.

Issue

Vol. 2 No. 1 (2019): Data Mining and Green Technology

Section

Articles

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DOI : https://doi.org/10.32877/bt.v2i1.92
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